instins— title: “time_series” author: “hy” date: “April 6, 2018” output: html_document —

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library(ggplot2)
library(tidyverse)
## Loading tidyverse: tibble
## Loading tidyverse: tidyr
## Loading tidyverse: readr
## Loading tidyverse: purrr
## Loading tidyverse: dplyr
## Conflicts with tidy packages ----------------------------------------------
## filter(): dplyr, stats
## lag():    dplyr, stats
library(plotly)
## 
## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
## 
##     last_plot
## The following object is masked from 'package:stats':
## 
##     filter
## The following object is masked from 'package:graphics':
## 
##     layout
library(data.table)
## 
## Attaching package: 'data.table'
## The following objects are masked from 'package:dplyr':
## 
##     between, first, last
## The following object is masked from 'package:purrr':
## 
##     transpose
library(dygraphs)
library(quantmod)
## Loading required package: xts
## Loading required package: zoo
## 
## Attaching package: 'zoo'
## The following objects are masked from 'package:base':
## 
##     as.Date, as.Date.numeric
## 
## Attaching package: 'xts'
## The following objects are masked from 'package:data.table':
## 
##     first, last
## The following objects are masked from 'package:dplyr':
## 
##     first, last
## Loading required package: TTR
## Version 0.4-0 included new data defaults. See ?getSymbols.
library(fpp)
## Loading required package: forecast
## Loading required package: fma
## Loading required package: expsmooth
## Loading required package: lmtest
## Loading required package: tseries
library(xts)
library(plyr)
## -------------------------------------------------------------------------
## You have loaded plyr after dplyr - this is likely to cause problems.
## If you need functions from both plyr and dplyr, please load plyr first, then dplyr:
## library(plyr); library(dplyr)
## -------------------------------------------------------------------------
## 
## Attaching package: 'plyr'
## The following object is masked from 'package:fma':
## 
##     ozone
## The following objects are masked from 'package:plotly':
## 
##     arrange, mutate, rename, summarise
## The following objects are masked from 'package:dplyr':
## 
##     arrange, count, desc, failwith, id, mutate, rename, summarise,
##     summarize
## The following object is masked from 'package:purrr':
## 
##     compact
all_metro <- read.csv("Metro_MedianRentalPrice_AllHomes.csv", stringsAsFactors = FALSE)
specific <- c("New York, NY", "Los Angeles, CA", "Chicago, IL", "Dallas, TX", "Philadelphia, PA", "Houston, TX",
              "Washington, DC", "Miami, FL", "Atlanta, GA", "San Francisco, CA", "Boston, MA", "Detroit, MI",
              "Phoenix, AZ", "Seattle, WA", "Minneapolis, MN", "Austin, TX", "San Jose, CA", "Denver, CO")
metro <- all_metro[all_metro$RegionName %in% specific,]


# transpose
tmetro <- transpose(metro)

# get row and colnames in order
colnames(tmetro) <- rownames(metro)
rownames(tmetro) <- colnames(metro)


setDT(tmetro, keep.rownames = TRUE)[]
##              rn            2               3           4          5
##   1: RegionName New York, NY Los Angeles, CA Chicago, IL Dallas, TX
##   2:   SizeRank            1               2           3          4
##   3:   X2010.01         2150              NA          NA         NA
##   4:   X2010.02         2000            2495        1550       1250
##   5:   X2010.03         2300            2400        1500       1300
##   6:   X2010.04         2500          2462.5        1500       1400
##   7:   X2010.05         2400            2500        1500       1350
##   8:   X2010.06         2650            2500        1500       1350
##   9:   X2010.07         2495          2699.5        1550       1350
##  10:   X2010.08         2300            2800        1500       1350
##  11:   X2010.09         2300            2600        1500       1375
##  12:   X2010.10         2500            2500        1560       1400
##  13:   X2010.11         2500            2500        1575       1395
##  14:   X2010.12         2800            2500        1600       1400
##  15:   X2011.01         2500            2495        1550       1375
##  16:   X2011.02         2400            2450        1525       1300
##  17:   X2011.03         2500            2450        1500       1300
##  18:   X2011.04         2700            2500        1550       1325
##  19:   X2011.05         2700            2500        1585       1350
##  20:   X2011.06         2700            2500        1600       1350
##  21:   X2011.07         2700            2500        1600       1350
##  22:   X2011.08         2700            2500        1600       1300
##  23:   X2011.09         2600            2500        1600       1295
##  24:   X2011.10         2500            2400        1550       1250
##  25:   X2011.11         2500            2300        1500       1250
##  26:   X2011.12         2500            2300        1500       1250
##  27:   X2012.01         2400            2300        1500       1250
##  28:   X2012.02         2535            2350        1500       1295
##  29:   X2012.03         2500            2300        1550       1300
##  30:   X2012.04         2500            2295        1500       1200
##  31:   X2012.05         2595            2350        1500       1250
##  32:   X2012.06         2550            2350        1550       1295
##  33:   X2012.07         2599            2300        1550       1257
##  34:   X2012.08         2575            2250        1550       1250
##  35:   X2012.09         2595            2300        1500       1250
##  36:   X2012.10         2600            2200        1500       1250
##  37:   X2012.11         2600            2150        1500     1273.5
##  38:   X2012.12         2750            2100        1500       1250
##  39:   X2013.01         2700            2175        1500       1225
##  40:   X2013.02         2750            2200        1500       1250
##  41:   X2013.03         2750            2150        1500       1250
##  42:   X2013.04         2800            2200        1500       1250
##  43:   X2013.05         2850            2200        1550       1275
##  44:   X2013.06         2800            2250        1550       1350
##  45:   X2013.07         2695            2200      1582.5       1350
##  46:   X2013.08         2700            2050        1595       1300
##  47:   X2013.09         2700            2300      1596.5       1345
##  48:   X2013.10         2600            2400        1600       1350
##  49:   X2013.11         2650            2300        1595       1325
##  50:   X2013.12         2750            2450        1600       1350
##  51:   X2014.01         2775            2400        1595       1350
##  52:   X2014.02         2750            2400        1557       1350
##  53:   X2014.03         2700            2400        1550       1350
##  54:   X2014.04         2675            2400        1550       1350
##  55:   X2014.05         2800            2500        1600       1400
##  56:   X2014.06         2850            2550        1650       1400
##  57:   X2014.07         2750            2600        1650       1450
##  58:   X2014.08         2700            2600        1650       1450
##  59:   X2014.09         2650            2600        1650       1445
##  60:   X2014.10         2600            2600        1650       1424
##  61:   X2014.11         2600            2600        1600       1445
##  62:   X2014.12         2650            2650        1609       1450
##  63:   X2015.01         2795            2650        1600       1450
##  64:   X2015.02         2795            2650        1625       1450
##  65:   X2015.03         2800            2685        1649       1495
##  66:   X2015.04         2900            2750        1650       1500
##  67:   X2015.05         2800            2795        1650       1500
##  68:   X2015.06         2850            2800        1650       1500
##  69:   X2015.07         2900            2800        1665       1550
##  70:   X2015.08         2900            2850        1675       1525
##  71:   X2015.09         2900            2800        1650       1500
##  72:   X2015.10         2800            2800        1609       1500
##  73:   X2015.11         2850            2800        1645       1500
##  74:   X2015.12         2900            2800        1600       1500
##  75:   X2016.01         2950            2800        1605       1500
##  76:   X2016.02         2899            2875        1645       1500
##  77:   X2016.03         2950            2900        1650       1550
##  78:   X2016.04         3000            2850        1650       1550
##  79:   X2016.05         3000            2800        1650       1550
##  80:   X2016.06         2900            2895        1650       1575
##  81:   X2016.07         2800            2850        1650       1595
##  82:   X2016.08         2700            2800        1650       1595
##  83:   X2016.09         2800            2870        1600       1545
##  84:   X2016.10         2800            2790        1600       1525
##  85:   X2016.11         2750            2900        1600       1595
##  86:   X2016.12         2700            2750        1600       1525
##  87:   X2017.01         2700            2850        1600       1595
##  88:   X2017.02         2750            2950        1600       1599
##  89:   X2017.03         2850            3000        1625       1625
##  90:   X2017.04         2975            3050        1650       1675
##  91:   X2017.05         3000            3100        1695       1695
##  92:   X2017.06         3000            3100        1700       1700
##  93:   X2017.07         2950            3100        1700       1700
##  94:   X2017.08         2895            3095        1700       1695
##  95:   X2017.09         3195            3000        1695       1695
##  96:   X2017.10         2950            3000        1650       1650
##  97:   X2017.11         2950            3000        1650       1650
##  98:   X2017.12         3000            3000        1650       1650
##  99:   X2018.01         2950            3000        1650       1650
## 100:   X2018.02         3000            3000        1650       1650
##              rn            2               3           4          5
##                     6           7              8         9          10
##   1: Philadelphia, PA Houston, TX Washington, DC Miami, FL Atlanta, GA
##   2:                5           6              7         8           9
##   3:               NA          NA             NA        NA      1012.5
##   4:             1500          NA           1650        NA        1150
##   5:             1500          NA           1700      1800        1195
##   6:             1497          NA           1750      1800        1200
##   7:             1500          NA           1750      1800        1200
##   8:           1537.5          NA           1800      1800        1200
##   9:             1500          NA           1900      1900        1200
##  10:             1500          NA           1875      1900        1200
##  11:             1500          NA           1800      1900        1200
##  12:             1495          NA           1800      1800        1200
##  13:             1500          NA           1800      1750        1200
##  14:             1500          NA           1800      1800        1200
##  15:             1400          NA           1800      1700        1175
##  16:             1400          NA           1800      1650        1150
##  17:             1400          NA           1800      1650        1150
##  18:             1500          NA           1845    1699.5        1195
##  19:             1500          NA           1900      1700        1200
##  20:             1500          NA           1950      1700        1200
##  21:             1500          NA           1945      1700        1150
##  22:             1500          NA           1900      1700        1150
##  23:             1500          NA           1900      1700        1100
##  24:             1450          NA           1900      1700        1100
##  25:             1400          NA           1850      1700        1099
##  26:             1400          NA           1850      1675        1100
##  27:             1400          NA           1825      1650        1050
##  28:             1400          NA           1800      1650        1050
##  29:             1450          NA           1850      1697        1085
##  30:             1450          NA           1895      1650        1040
##  31:             1450          NA           1925      1650        1050
##  32:             1450          NA           1990      1700        1095
##  33:             1400          NA           1975      1690        1095
##  34:             1400          NA           1950      1695        1050
##  35:             1375          NA           1900      1650        1075
##  36:             1380          NA           1900      1650        1050
##  37:             1375          NA           1900      1650        1000
##  38:             1350          NA           1899      1650        1000
##  39:             1350          NA           1895      1650        1000
##  40:             1350          NA           1900      1650         995
##  41:             1375          NA           1900      1650        1015
##  42:             1400          NA           1900      1695        1045
##  43:             1450          NA           1900      1700        1095
##  44:             1400          NA           1995      1750        1095
##  45:             1400          NA           1975      1800        1095
##  46:             1400          NA           1960      1800        1050
##  47:             1400          NA           1950      1800        1095
##  48:             1425          NA           1950      1850        1100
##  49:             1400        1375           1950      1875        1090
##  50:             1400        1395           1900      1900        1100
##  51:             1400        1375           1900      1850        1095
##  52:             1375        1355           1900      1850        1095
##  53:             1395        1395           1900      1800        1095
##  54:             1400        1450           1900      1800        1095
##  55:             1500        1500           1995      1850        1100
##  56:             1500        1550           2000      1850        1100
##  57:             1500        1550           2000      1875        1125
##  58:             1500        1575           2000      1850        1149
##  59:             1495        1550           2000      1850        1149
##  60:             1475        1525           1980      1850        1150
##  61:             1450        1550           1950      1850        1150
##  62:             1450        1550           1950      1850        1125
##  63:             1450        1550           1950      1850        1125
##  64:             1495        1550           1950      1850        1145
##  65:             1500        1575           1975      1900        1175
##  66:             1500        1600           1995      1900        1200
##  67:             1550        1600           2000      1950        1200
##  68:             1550        1650           2050      2000        1250
##  69:             1550        1625           2050      2000        1245
##  70:             1500        1600           2050      2000        1200
##  71:             1500        1600           2000      1995        1200
##  72:             1500        1600           1999      2000        1200
##  73:             1500        1600           1995      2000        1200
##  74:             1475        1600           1995      2000        1200
##  75:             1495        1600           1995      2000        1225
##  76:             1500        1600           1999      2000        1240
##  77:             1500        1645           2000      2000        1250
##  78:             1550        1650           2000      2000        1260
##  79:             1550        1600           2050      2000        1300
##  80:             1525        1600           2050      2000        1300
##  81:             1500        1575           2100      1950        1300
##  82:             1500        1585           2099      1900        1295
##  83:             1500      1556.5           2000      1950        1295
##  84:             1450        1500           2000      1950        1300
##  85:             1495        1505           1999      2000        1300
##  86:             1450        1495           1999      1875        1295
##  87:             1450        1525           2000      1930        1300
##  88:             1450        1550           2000      1950        1345
##  89:             1500        1550           2000      1975        1350
##  90:             1550        1595           2100      1995        1400
##  91:             1550        1600           2150      2000        1400
##  92:             1550        1600           2195      2000      1418.5
##  93:             1550        1600           2200      2000        1445
##  94:             1500        1600           2150      2000        1400
##  95:             1500        1600           2100      2000        1400
##  96:             1500        1595           2050      2000        1395
##  97:             1500        1590           2000      2000        1395
##  98:             1500        1595           2000      2000        1395
##  99:             1500        1575           2000      2000        1400
## 100:             1500        1591           2000      2000        1400
##                     6           7              8         9          10
##              11                12          13          15          16
##   1: Boston, MA San Francisco, CA Detroit, MI Phoenix, AZ Seattle, WA
##   2:         10                11          12          14          15
##   3:         NA              2600          NA          NA        1200
##   4:         NA              2250          NA          NA        1395
##   5:       1375              2200          NA        1500        1495
##   6:       1500              2250          NA        1495        1500
##   7:       1475              2600          NA        1400        1500
##   8:     1552.5              2500          NA        1350        1595
##   9:     1597.5              2575          NA        1300        1600
##  10:       1600            2397.5          NA        1300        1685
##  11:       1600              2150          NA        1295        1600
##  12:       1600              2150          NA        1275        1595
##  13:       1691              2100          NA        1275        1550
##  14:       1695              2200          NA        1250      1499.5
##  15:     1747.5              2000          NA        1195        1550
##  16:     1707.5              2050          NA        1175        1500
##  17:     1747.5              2095          NA        1150        1500
##  18:       1850              2100          NA        1195        1525
##  19:       1900              2075          NA        1195        1595
##  20:       1900              2100          NA        1175        1595
##  21:       1975            2167.5          NA        1125        1595
##  22:       1900              2150          NA        1100        1550
##  23:       1900              2150          NA        1100        1550
##  24:     1837.5              2150          NA        1100        1500
##  25:       1850              2150         800        1095        1450
##  26:       1850              2050         850        1095      1401.5
##  27:       1900              2000         850        1099        1400
##  28:       1950              2095         850        1095        1400
##  29:       2000              2200         850        1100        1450
##  30:       2000              1995         850        1100        1450
##  31:       2050              1950         850        1120        1475
##  32:       2100              2050         850        1150        1495
##  33:       2100              2000         850        1125        1495
##  34:       2000              1995         895        1100        1495
##  35:       2150              2000         875        1100        1475
##  36:       2100              2000         850        1100        1450
##  37:       2100              2000         850        1095      1407.5
##  38:       2070              2000         850        1095        1395
##  39:       2200              2000         850        1098        1395
##  40:       2200              2000         850        1095        1385
##  41:       2200              2000         850        1100        1395
##  42:       2250              1995         850        1100        1449
##  43:       2250              2000         870        1100        1495
##  44:       2297              2000         850        1100        1525
##  45:       2300              2050         875        1100        1500
##  46:       2250              2000         875        1070        1550
##  47:       2200              2200         899        1100        1595
##  48:       2325              2200         899        1100        1625
##  49:       2300              2200         900        1100        1625
##  50:       2300              2300         900        1100        1600
##  51:       2310              2295         900        1100        1595
##  52:       2300              2250         895        1100        1595
##  53:       2300              2275         895        1100        1595
##  54:       2350              2300         899        1125        1595
##  55:       2500              2500         900        1200        1650
##  56:       2500              2500         900        1200        1650
##  57:       2500              2650         900        1200        1695
##  58:       2450              2700         925        1200        1700
##  59:       2400              2700         900        1200        1695
##  60:       2365              2700         925        1200        1695
##  61:       2325              2750         925        1200        1695
##  62:       2400              2750         925        1200        1690
##  63:       2500              2700         900        1200        1675
##  64:       2500            2799.5         900        1250        1690
##  65:       2500              2850       912.5        1290        1695
##  66:       2500            2922.5         950        1299        1695
##  67:       2500              3000         950        1299        1750
##  68:       2500              3100         950        1300        1795
##  69:       2500              3200         950        1295        1850
##  70:       2500              3100         950        1295        1895
##  71:       2450              3100         950        1295        1850
##  72:       2400              3150         950        1275        1850
##  73:       2400              3150         950        1295        1850
##  74:     2499.5            3154.5         950        1300        1850
##  75:       2600              3200         950        1300        1850
##  76:       2600              3250         950        1325        1850
##  77:       2600              3300         975        1350        1850
##  78:       2550              3300        1000        1350        1850
##  79:       2500              3250        1000        1300        1900
##  80:       2600              3250        1000        1300        1975
##  81:       2500              3300        1100        1299        2000
##  82:       2500              3200        1095        1295        2000
##  83:       2500              3195        1000        1275        1995
##  84:       2450              3000        1049        1295        1950
##  85:       2400              3000        1040        1295      1949.5
##  86:       2450              2995        1000        1250        1900
##  87:       2500              3000        1000        1300        1995
##  88:       2600              3195         995        1325        2025
##  89:       2600              3200        1000        1350        2100
##  90:       2650              3300        1050        1399        2195
##  91:       2645              3400        1075        1400        2250
##  92:       2600              3400        1100        1400        2300
##  93:       2600              3400        1100        1400        2350
##  94:       2600              3400        1100        1400        2300
##  95:       2502              3300        1100        1395        2295
##  96:       2500              3295        1050        1395        2200
##  97:       2500              3200        1050        1395        2195
##  98:       2515              3200        1025        1395        2195
##  99:       2600              3200        1000        1395        2195
## 100:       2600              3200        1050        1400        2200
##              11                12          13          15          16
##                   17         22           35         36
##   1: Minneapolis, MN Denver, CO San Jose, CA Austin, TX
##   2:              16         21           34         35
##   3:              NA         NA           NA         NA
##   4:              NA         NA           NA         NA
##   5:              NA         NA           NA         NA
##   6:              NA         NA           NA         NA
##   7:              NA     1672.5           NA         NA
##   8:              NA     1392.5           NA         NA
##   9:              NA       1450           NA         NA
##  10:              NA       1390           NA         NA
##  11:            1400     1297.5           NA         NA
##  12:            1400       1250           NA         NA
##  13:            1399       1350           NA         NA
##  14:            1450       1300           NA         NA
##  15:            1300     1297.5           NA         NA
##  16:            1350       1300         2195         NA
##  17:            1350       1350         2295         NA
##  18:            1395       1350         2380         NA
##  19:            1385       1375         2380         NA
##  20:            1377       1350         2400         NA
##  21:            1395       1350         2500         NA
##  22:            1395       1350         2500         NA
##  23:            1390       1355         2495         NA
##  24:            1350       1350         2400         NA
##  25:            1300       1300         2395         NA
##  26:            1295       1295         2300         NA
##  27:            1295       1295         2250         NA
##  28:            1300       1295         2275         NA
##  29:            1300       1300         2300         NA
##  30:            1300       1395         2295         NA
##  31:            1300       1395         2250         NA
##  32:            1350       1400         2300         NA
##  33:            1325       1400         2400         NA
##  34:            1300       1400         2350         NA
##  35:            1375       1400         2350         NA
##  36:            1375       1375         2400         NA
##  37:            1300       1325         2300         NA
##  38:            1350       1310         2347         NA
##  39:            1350       1350         2370         NA
##  40:            1350       1350         2300       1100
##  41:            1350     1390.5       2295.5       1024
##  42:            1350       1450         2349       1090
##  43:            1350       1395         2400       1115
##  44:            1350       1395         2400     1281.5
##  45:            1300       1500         2500       1150
##  46:            1315       1475         2431       1199
##  47:            1375       1500         2650       1285
##  48:            1395       1575         2780       1349
##  49:            1400       1595         2775       1350
##  50:            1400       1600         2800       1326
##  51:            1400       1595         2695       1325
##  52:            1400       1575         2650       1350
##  53:            1395       1550         2650       1395
##  54:            1395       1595         2700     1419.5
##  55:            1395       1600         2995       1400
##  56:            1400       1695         3000       1400
##  57:            1400       1695         3095       1450
##  58:            1400       1700         3200       1450
##  59:            1400       1790         3150       1418
##  60:            1399     1754.5         3050       1400
##  61:            1399       1789       3072.5       1395
##  62:            1400       1750         3000       1395
##  63:            1400       1789         3000       1399
##  64:            1399       1800         3100       1400
##  65:            1400       1845         3200       1400
##  66:            1425       1850         3200       1450
##  67:            1450       1895       3352.5       1495
##  68:          1456.5       1895         3500       1500
##  69:            1450       1895         3500       1525
##  70:            1450       1929         3500       1525
##  71:            1450       1900         3500       1525
##  72:            1450       1895         3495     1532.5
##  73:            1450       1850         3400       1529
##  74:            1450       1850         3300       1500
##  75:            1475       1895         3395       1500
##  76:            1475       1895         3495       1500
##  77:            1480       1900         3450       1500
##  78:            1450       1890         3400       1450
##  79:            1450       1900         3500       1450
##  80:            1475       1900         3495       1495
##  81:            1495       1895         3500       1499
##  82:            1450       1900         3400       1499
##  83:            1450       1850         3300       1445
##  84:            1450       1850       3292.5       1400
##  85:            1495       1800         3200       1400
##  86:            1450       1800         3200       1400
##  87:            1497       1850         3250       1500
##  88:            1500       1895         3300       1550
##  89:            1525       1900       3399.5       1595
##  90:          1529.5       1950         3450       1625
##  91:            1575       1995         3500       1650
##  92:            1579       1995         3600       1650
##  93:            1595       1995         3600       1650
##  94:            1595       1950         3500       1625
##  95:            1595       1950         3500       1600
##  96:            1563       1950         3480       1600
##  97:            1600       1950         3400       1595
##  98:            1600       1950         3450       1595
##  99:            1600       1950         3480       1595
## 100:            1600       1995         3485       1600
##                   17         22           35         36
colnames(tmetro)[1] <- "date"

names(tmetro) <- as.matrix(tmetro[1, ])
tmetro <- tmetro[-1, ]
tmetro[] <- lapply(tmetro, function(x) type.convert(as.character(x)))

tmetro <- tail(tmetro,-1)
tmetro$RegionName <- substr(tmetro$RegionName,2,8)
tmetro$RegionName <- paste(paste(substr(tmetro$RegionName,1,4), "-"),substr(tmetro$RegionName,6,7) )

tmetro$RegionName <- gsub(" ", "", tmetro$RegionName, fixed = TRUE)
tmetro$RegionName <- paste(tmetro$RegionName, "-01", sep = '')
tmetro$RegionName <- as.Date(as.character(tmetro$RegionName,"%Y-%m-%d"))

tmetro
##     RegionName New York, NY Los Angeles, CA Chicago, IL Dallas, TX
##  1: 2010-01-01         2150              NA          NA         NA
##  2: 2010-02-01         2000          2495.0      1550.0     1250.0
##  3: 2010-03-01         2300          2400.0      1500.0     1300.0
##  4: 2010-04-01         2500          2462.5      1500.0     1400.0
##  5: 2010-05-01         2400          2500.0      1500.0     1350.0
##  6: 2010-06-01         2650          2500.0      1500.0     1350.0
##  7: 2010-07-01         2495          2699.5      1550.0     1350.0
##  8: 2010-08-01         2300          2800.0      1500.0     1350.0
##  9: 2010-09-01         2300          2600.0      1500.0     1375.0
## 10: 2010-10-01         2500          2500.0      1560.0     1400.0
## 11: 2010-11-01         2500          2500.0      1575.0     1395.0
## 12: 2010-12-01         2800          2500.0      1600.0     1400.0
## 13: 2011-01-01         2500          2495.0      1550.0     1375.0
## 14: 2011-02-01         2400          2450.0      1525.0     1300.0
## 15: 2011-03-01         2500          2450.0      1500.0     1300.0
## 16: 2011-04-01         2700          2500.0      1550.0     1325.0
## 17: 2011-05-01         2700          2500.0      1585.0     1350.0
## 18: 2011-06-01         2700          2500.0      1600.0     1350.0
## 19: 2011-07-01         2700          2500.0      1600.0     1350.0
## 20: 2011-08-01         2700          2500.0      1600.0     1300.0
## 21: 2011-09-01         2600          2500.0      1600.0     1295.0
## 22: 2011-10-01         2500          2400.0      1550.0     1250.0
## 23: 2011-11-01         2500          2300.0      1500.0     1250.0
## 24: 2011-12-01         2500          2300.0      1500.0     1250.0
## 25: 2012-01-01         2400          2300.0      1500.0     1250.0
## 26: 2012-02-01         2535          2350.0      1500.0     1295.0
## 27: 2012-03-01         2500          2300.0      1550.0     1300.0
## 28: 2012-04-01         2500          2295.0      1500.0     1200.0
## 29: 2012-05-01         2595          2350.0      1500.0     1250.0
## 30: 2012-06-01         2550          2350.0      1550.0     1295.0
## 31: 2012-07-01         2599          2300.0      1550.0     1257.0
## 32: 2012-08-01         2575          2250.0      1550.0     1250.0
## 33: 2012-09-01         2595          2300.0      1500.0     1250.0
## 34: 2012-10-01         2600          2200.0      1500.0     1250.0
## 35: 2012-11-01         2600          2150.0      1500.0     1273.5
## 36: 2012-12-01         2750          2100.0      1500.0     1250.0
## 37: 2013-01-01         2700          2175.0      1500.0     1225.0
## 38: 2013-02-01         2750          2200.0      1500.0     1250.0
## 39: 2013-03-01         2750          2150.0      1500.0     1250.0
## 40: 2013-04-01         2800          2200.0      1500.0     1250.0
## 41: 2013-05-01         2850          2200.0      1550.0     1275.0
## 42: 2013-06-01         2800          2250.0      1550.0     1350.0
## 43: 2013-07-01         2695          2200.0      1582.5     1350.0
## 44: 2013-08-01         2700          2050.0      1595.0     1300.0
## 45: 2013-09-01         2700          2300.0      1596.5     1345.0
## 46: 2013-10-01         2600          2400.0      1600.0     1350.0
## 47: 2013-11-01         2650          2300.0      1595.0     1325.0
## 48: 2013-12-01         2750          2450.0      1600.0     1350.0
## 49: 2014-01-01         2775          2400.0      1595.0     1350.0
## 50: 2014-02-01         2750          2400.0      1557.0     1350.0
## 51: 2014-03-01         2700          2400.0      1550.0     1350.0
## 52: 2014-04-01         2675          2400.0      1550.0     1350.0
## 53: 2014-05-01         2800          2500.0      1600.0     1400.0
## 54: 2014-06-01         2850          2550.0      1650.0     1400.0
## 55: 2014-07-01         2750          2600.0      1650.0     1450.0
## 56: 2014-08-01         2700          2600.0      1650.0     1450.0
## 57: 2014-09-01         2650          2600.0      1650.0     1445.0
## 58: 2014-10-01         2600          2600.0      1650.0     1424.0
## 59: 2014-11-01         2600          2600.0      1600.0     1445.0
## 60: 2014-12-01         2650          2650.0      1609.0     1450.0
## 61: 2015-01-01         2795          2650.0      1600.0     1450.0
## 62: 2015-02-01         2795          2650.0      1625.0     1450.0
## 63: 2015-03-01         2800          2685.0      1649.0     1495.0
## 64: 2015-04-01         2900          2750.0      1650.0     1500.0
## 65: 2015-05-01         2800          2795.0      1650.0     1500.0
## 66: 2015-06-01         2850          2800.0      1650.0     1500.0
## 67: 2015-07-01         2900          2800.0      1665.0     1550.0
## 68: 2015-08-01         2900          2850.0      1675.0     1525.0
## 69: 2015-09-01         2900          2800.0      1650.0     1500.0
## 70: 2015-10-01         2800          2800.0      1609.0     1500.0
## 71: 2015-11-01         2850          2800.0      1645.0     1500.0
## 72: 2015-12-01         2900          2800.0      1600.0     1500.0
## 73: 2016-01-01         2950          2800.0      1605.0     1500.0
## 74: 2016-02-01         2899          2875.0      1645.0     1500.0
## 75: 2016-03-01         2950          2900.0      1650.0     1550.0
## 76: 2016-04-01         3000          2850.0      1650.0     1550.0
## 77: 2016-05-01         3000          2800.0      1650.0     1550.0
## 78: 2016-06-01         2900          2895.0      1650.0     1575.0
## 79: 2016-07-01         2800          2850.0      1650.0     1595.0
## 80: 2016-08-01         2700          2800.0      1650.0     1595.0
## 81: 2016-09-01         2800          2870.0      1600.0     1545.0
## 82: 2016-10-01         2800          2790.0      1600.0     1525.0
## 83: 2016-11-01         2750          2900.0      1600.0     1595.0
## 84: 2016-12-01         2700          2750.0      1600.0     1525.0
## 85: 2017-01-01         2700          2850.0      1600.0     1595.0
## 86: 2017-02-01         2750          2950.0      1600.0     1599.0
## 87: 2017-03-01         2850          3000.0      1625.0     1625.0
## 88: 2017-04-01         2975          3050.0      1650.0     1675.0
## 89: 2017-05-01         3000          3100.0      1695.0     1695.0
## 90: 2017-06-01         3000          3100.0      1700.0     1700.0
## 91: 2017-07-01         2950          3100.0      1700.0     1700.0
## 92: 2017-08-01         2895          3095.0      1700.0     1695.0
## 93: 2017-09-01         3195          3000.0      1695.0     1695.0
## 94: 2017-10-01         2950          3000.0      1650.0     1650.0
## 95: 2017-11-01         2950          3000.0      1650.0     1650.0
## 96: 2017-12-01         3000          3000.0      1650.0     1650.0
## 97: 2018-01-01         2950          3000.0      1650.0     1650.0
## 98: 2018-02-01         3000          3000.0      1650.0     1650.0
##     RegionName New York, NY Los Angeles, CA Chicago, IL Dallas, TX
##     Philadelphia, PA Houston, TX Washington, DC Miami, FL Atlanta, GA
##  1:               NA          NA             NA        NA      1012.5
##  2:           1500.0          NA           1650        NA      1150.0
##  3:           1500.0          NA           1700    1800.0      1195.0
##  4:           1497.0          NA           1750    1800.0      1200.0
##  5:           1500.0          NA           1750    1800.0      1200.0
##  6:           1537.5          NA           1800    1800.0      1200.0
##  7:           1500.0          NA           1900    1900.0      1200.0
##  8:           1500.0          NA           1875    1900.0      1200.0
##  9:           1500.0          NA           1800    1900.0      1200.0
## 10:           1495.0          NA           1800    1800.0      1200.0
## 11:           1500.0          NA           1800    1750.0      1200.0
## 12:           1500.0          NA           1800    1800.0      1200.0
## 13:           1400.0          NA           1800    1700.0      1175.0
## 14:           1400.0          NA           1800    1650.0      1150.0
## 15:           1400.0          NA           1800    1650.0      1150.0
## 16:           1500.0          NA           1845    1699.5      1195.0
## 17:           1500.0          NA           1900    1700.0      1200.0
## 18:           1500.0          NA           1950    1700.0      1200.0
## 19:           1500.0          NA           1945    1700.0      1150.0
## 20:           1500.0          NA           1900    1700.0      1150.0
## 21:           1500.0          NA           1900    1700.0      1100.0
## 22:           1450.0          NA           1900    1700.0      1100.0
## 23:           1400.0          NA           1850    1700.0      1099.0
## 24:           1400.0          NA           1850    1675.0      1100.0
## 25:           1400.0          NA           1825    1650.0      1050.0
## 26:           1400.0          NA           1800    1650.0      1050.0
## 27:           1450.0          NA           1850    1697.0      1085.0
## 28:           1450.0          NA           1895    1650.0      1040.0
## 29:           1450.0          NA           1925    1650.0      1050.0
## 30:           1450.0          NA           1990    1700.0      1095.0
## 31:           1400.0          NA           1975    1690.0      1095.0
## 32:           1400.0          NA           1950    1695.0      1050.0
## 33:           1375.0          NA           1900    1650.0      1075.0
## 34:           1380.0          NA           1900    1650.0      1050.0
## 35:           1375.0          NA           1900    1650.0      1000.0
## 36:           1350.0          NA           1899    1650.0      1000.0
## 37:           1350.0          NA           1895    1650.0      1000.0
## 38:           1350.0          NA           1900    1650.0       995.0
## 39:           1375.0          NA           1900    1650.0      1015.0
## 40:           1400.0          NA           1900    1695.0      1045.0
## 41:           1450.0          NA           1900    1700.0      1095.0
## 42:           1400.0          NA           1995    1750.0      1095.0
## 43:           1400.0          NA           1975    1800.0      1095.0
## 44:           1400.0          NA           1960    1800.0      1050.0
## 45:           1400.0          NA           1950    1800.0      1095.0
## 46:           1425.0          NA           1950    1850.0      1100.0
## 47:           1400.0      1375.0           1950    1875.0      1090.0
## 48:           1400.0      1395.0           1900    1900.0      1100.0
## 49:           1400.0      1375.0           1900    1850.0      1095.0
## 50:           1375.0      1355.0           1900    1850.0      1095.0
## 51:           1395.0      1395.0           1900    1800.0      1095.0
## 52:           1400.0      1450.0           1900    1800.0      1095.0
## 53:           1500.0      1500.0           1995    1850.0      1100.0
## 54:           1500.0      1550.0           2000    1850.0      1100.0
## 55:           1500.0      1550.0           2000    1875.0      1125.0
## 56:           1500.0      1575.0           2000    1850.0      1149.0
## 57:           1495.0      1550.0           2000    1850.0      1149.0
## 58:           1475.0      1525.0           1980    1850.0      1150.0
## 59:           1450.0      1550.0           1950    1850.0      1150.0
## 60:           1450.0      1550.0           1950    1850.0      1125.0
## 61:           1450.0      1550.0           1950    1850.0      1125.0
## 62:           1495.0      1550.0           1950    1850.0      1145.0
## 63:           1500.0      1575.0           1975    1900.0      1175.0
## 64:           1500.0      1600.0           1995    1900.0      1200.0
## 65:           1550.0      1600.0           2000    1950.0      1200.0
## 66:           1550.0      1650.0           2050    2000.0      1250.0
## 67:           1550.0      1625.0           2050    2000.0      1245.0
## 68:           1500.0      1600.0           2050    2000.0      1200.0
## 69:           1500.0      1600.0           2000    1995.0      1200.0
## 70:           1500.0      1600.0           1999    2000.0      1200.0
## 71:           1500.0      1600.0           1995    2000.0      1200.0
## 72:           1475.0      1600.0           1995    2000.0      1200.0
## 73:           1495.0      1600.0           1995    2000.0      1225.0
## 74:           1500.0      1600.0           1999    2000.0      1240.0
## 75:           1500.0      1645.0           2000    2000.0      1250.0
## 76:           1550.0      1650.0           2000    2000.0      1260.0
## 77:           1550.0      1600.0           2050    2000.0      1300.0
## 78:           1525.0      1600.0           2050    2000.0      1300.0
## 79:           1500.0      1575.0           2100    1950.0      1300.0
## 80:           1500.0      1585.0           2099    1900.0      1295.0
## 81:           1500.0      1556.5           2000    1950.0      1295.0
## 82:           1450.0      1500.0           2000    1950.0      1300.0
## 83:           1495.0      1505.0           1999    2000.0      1300.0
## 84:           1450.0      1495.0           1999    1875.0      1295.0
## 85:           1450.0      1525.0           2000    1930.0      1300.0
## 86:           1450.0      1550.0           2000    1950.0      1345.0
## 87:           1500.0      1550.0           2000    1975.0      1350.0
## 88:           1550.0      1595.0           2100    1995.0      1400.0
## 89:           1550.0      1600.0           2150    2000.0      1400.0
## 90:           1550.0      1600.0           2195    2000.0      1418.5
## 91:           1550.0      1600.0           2200    2000.0      1445.0
## 92:           1500.0      1600.0           2150    2000.0      1400.0
## 93:           1500.0      1600.0           2100    2000.0      1400.0
## 94:           1500.0      1595.0           2050    2000.0      1395.0
## 95:           1500.0      1590.0           2000    2000.0      1395.0
## 96:           1500.0      1595.0           2000    2000.0      1395.0
## 97:           1500.0      1575.0           2000    2000.0      1400.0
## 98:           1500.0      1591.0           2000    2000.0      1400.0
##     Philadelphia, PA Houston, TX Washington, DC Miami, FL Atlanta, GA
##     Boston, MA San Francisco, CA Detroit, MI Phoenix, AZ Seattle, WA
##  1:         NA            2600.0          NA          NA      1200.0
##  2:         NA            2250.0          NA          NA      1395.0
##  3:     1375.0            2200.0          NA        1500      1495.0
##  4:     1500.0            2250.0          NA        1495      1500.0
##  5:     1475.0            2600.0          NA        1400      1500.0
##  6:     1552.5            2500.0          NA        1350      1595.0
##  7:     1597.5            2575.0          NA        1300      1600.0
##  8:     1600.0            2397.5          NA        1300      1685.0
##  9:     1600.0            2150.0          NA        1295      1600.0
## 10:     1600.0            2150.0          NA        1275      1595.0
## 11:     1691.0            2100.0          NA        1275      1550.0
## 12:     1695.0            2200.0          NA        1250      1499.5
## 13:     1747.5            2000.0          NA        1195      1550.0
## 14:     1707.5            2050.0          NA        1175      1500.0
## 15:     1747.5            2095.0          NA        1150      1500.0
## 16:     1850.0            2100.0          NA        1195      1525.0
## 17:     1900.0            2075.0          NA        1195      1595.0
## 18:     1900.0            2100.0          NA        1175      1595.0
## 19:     1975.0            2167.5          NA        1125      1595.0
## 20:     1900.0            2150.0          NA        1100      1550.0
## 21:     1900.0            2150.0          NA        1100      1550.0
## 22:     1837.5            2150.0          NA        1100      1500.0
## 23:     1850.0            2150.0       800.0        1095      1450.0
## 24:     1850.0            2050.0       850.0        1095      1401.5
## 25:     1900.0            2000.0       850.0        1099      1400.0
## 26:     1950.0            2095.0       850.0        1095      1400.0
## 27:     2000.0            2200.0       850.0        1100      1450.0
## 28:     2000.0            1995.0       850.0        1100      1450.0
## 29:     2050.0            1950.0       850.0        1120      1475.0
## 30:     2100.0            2050.0       850.0        1150      1495.0
## 31:     2100.0            2000.0       850.0        1125      1495.0
## 32:     2000.0            1995.0       895.0        1100      1495.0
## 33:     2150.0            2000.0       875.0        1100      1475.0
## 34:     2100.0            2000.0       850.0        1100      1450.0
## 35:     2100.0            2000.0       850.0        1095      1407.5
## 36:     2070.0            2000.0       850.0        1095      1395.0
## 37:     2200.0            2000.0       850.0        1098      1395.0
## 38:     2200.0            2000.0       850.0        1095      1385.0
## 39:     2200.0            2000.0       850.0        1100      1395.0
## 40:     2250.0            1995.0       850.0        1100      1449.0
## 41:     2250.0            2000.0       870.0        1100      1495.0
## 42:     2297.0            2000.0       850.0        1100      1525.0
## 43:     2300.0            2050.0       875.0        1100      1500.0
## 44:     2250.0            2000.0       875.0        1070      1550.0
## 45:     2200.0            2200.0       899.0        1100      1595.0
## 46:     2325.0            2200.0       899.0        1100      1625.0
## 47:     2300.0            2200.0       900.0        1100      1625.0
## 48:     2300.0            2300.0       900.0        1100      1600.0
## 49:     2310.0            2295.0       900.0        1100      1595.0
## 50:     2300.0            2250.0       895.0        1100      1595.0
## 51:     2300.0            2275.0       895.0        1100      1595.0
## 52:     2350.0            2300.0       899.0        1125      1595.0
## 53:     2500.0            2500.0       900.0        1200      1650.0
## 54:     2500.0            2500.0       900.0        1200      1650.0
## 55:     2500.0            2650.0       900.0        1200      1695.0
## 56:     2450.0            2700.0       925.0        1200      1700.0
## 57:     2400.0            2700.0       900.0        1200      1695.0
## 58:     2365.0            2700.0       925.0        1200      1695.0
## 59:     2325.0            2750.0       925.0        1200      1695.0
## 60:     2400.0            2750.0       925.0        1200      1690.0
## 61:     2500.0            2700.0       900.0        1200      1675.0
## 62:     2500.0            2799.5       900.0        1250      1690.0
## 63:     2500.0            2850.0       912.5        1290      1695.0
## 64:     2500.0            2922.5       950.0        1299      1695.0
## 65:     2500.0            3000.0       950.0        1299      1750.0
## 66:     2500.0            3100.0       950.0        1300      1795.0
## 67:     2500.0            3200.0       950.0        1295      1850.0
## 68:     2500.0            3100.0       950.0        1295      1895.0
## 69:     2450.0            3100.0       950.0        1295      1850.0
## 70:     2400.0            3150.0       950.0        1275      1850.0
## 71:     2400.0            3150.0       950.0        1295      1850.0
## 72:     2499.5            3154.5       950.0        1300      1850.0
## 73:     2600.0            3200.0       950.0        1300      1850.0
## 74:     2600.0            3250.0       950.0        1325      1850.0
## 75:     2600.0            3300.0       975.0        1350      1850.0
## 76:     2550.0            3300.0      1000.0        1350      1850.0
## 77:     2500.0            3250.0      1000.0        1300      1900.0
## 78:     2600.0            3250.0      1000.0        1300      1975.0
## 79:     2500.0            3300.0      1100.0        1299      2000.0
## 80:     2500.0            3200.0      1095.0        1295      2000.0
## 81:     2500.0            3195.0      1000.0        1275      1995.0
## 82:     2450.0            3000.0      1049.0        1295      1950.0
## 83:     2400.0            3000.0      1040.0        1295      1949.5
## 84:     2450.0            2995.0      1000.0        1250      1900.0
## 85:     2500.0            3000.0      1000.0        1300      1995.0
## 86:     2600.0            3195.0       995.0        1325      2025.0
## 87:     2600.0            3200.0      1000.0        1350      2100.0
## 88:     2650.0            3300.0      1050.0        1399      2195.0
## 89:     2645.0            3400.0      1075.0        1400      2250.0
## 90:     2600.0            3400.0      1100.0        1400      2300.0
## 91:     2600.0            3400.0      1100.0        1400      2350.0
## 92:     2600.0            3400.0      1100.0        1400      2300.0
## 93:     2502.0            3300.0      1100.0        1395      2295.0
## 94:     2500.0            3295.0      1050.0        1395      2200.0
## 95:     2500.0            3200.0      1050.0        1395      2195.0
## 96:     2515.0            3200.0      1025.0        1395      2195.0
## 97:     2600.0            3200.0      1000.0        1395      2195.0
## 98:     2600.0            3200.0      1050.0        1400      2200.0
##     Boston, MA San Francisco, CA Detroit, MI Phoenix, AZ Seattle, WA
##     Minneapolis, MN Denver, CO San Jose, CA Austin, TX
##  1:              NA         NA           NA         NA
##  2:              NA         NA           NA         NA
##  3:              NA         NA           NA         NA
##  4:              NA         NA           NA         NA
##  5:              NA     1672.5           NA         NA
##  6:              NA     1392.5           NA         NA
##  7:              NA     1450.0           NA         NA
##  8:              NA     1390.0           NA         NA
##  9:          1400.0     1297.5           NA         NA
## 10:          1400.0     1250.0           NA         NA
## 11:          1399.0     1350.0           NA         NA
## 12:          1450.0     1300.0           NA         NA
## 13:          1300.0     1297.5           NA         NA
## 14:          1350.0     1300.0       2195.0         NA
## 15:          1350.0     1350.0       2295.0         NA
## 16:          1395.0     1350.0       2380.0         NA
## 17:          1385.0     1375.0       2380.0         NA
## 18:          1377.0     1350.0       2400.0         NA
## 19:          1395.0     1350.0       2500.0         NA
## 20:          1395.0     1350.0       2500.0         NA
## 21:          1390.0     1355.0       2495.0         NA
## 22:          1350.0     1350.0       2400.0         NA
## 23:          1300.0     1300.0       2395.0         NA
## 24:          1295.0     1295.0       2300.0         NA
## 25:          1295.0     1295.0       2250.0         NA
## 26:          1300.0     1295.0       2275.0         NA
## 27:          1300.0     1300.0       2300.0         NA
## 28:          1300.0     1395.0       2295.0         NA
## 29:          1300.0     1395.0       2250.0         NA
## 30:          1350.0     1400.0       2300.0         NA
## 31:          1325.0     1400.0       2400.0         NA
## 32:          1300.0     1400.0       2350.0         NA
## 33:          1375.0     1400.0       2350.0         NA
## 34:          1375.0     1375.0       2400.0         NA
## 35:          1300.0     1325.0       2300.0         NA
## 36:          1350.0     1310.0       2347.0         NA
## 37:          1350.0     1350.0       2370.0         NA
## 38:          1350.0     1350.0       2300.0     1100.0
## 39:          1350.0     1390.5       2295.5     1024.0
## 40:          1350.0     1450.0       2349.0     1090.0
## 41:          1350.0     1395.0       2400.0     1115.0
## 42:          1350.0     1395.0       2400.0     1281.5
## 43:          1300.0     1500.0       2500.0     1150.0
## 44:          1315.0     1475.0       2431.0     1199.0
## 45:          1375.0     1500.0       2650.0     1285.0
## 46:          1395.0     1575.0       2780.0     1349.0
## 47:          1400.0     1595.0       2775.0     1350.0
## 48:          1400.0     1600.0       2800.0     1326.0
## 49:          1400.0     1595.0       2695.0     1325.0
## 50:          1400.0     1575.0       2650.0     1350.0
## 51:          1395.0     1550.0       2650.0     1395.0
## 52:          1395.0     1595.0       2700.0     1419.5
## 53:          1395.0     1600.0       2995.0     1400.0
## 54:          1400.0     1695.0       3000.0     1400.0
## 55:          1400.0     1695.0       3095.0     1450.0
## 56:          1400.0     1700.0       3200.0     1450.0
## 57:          1400.0     1790.0       3150.0     1418.0
## 58:          1399.0     1754.5       3050.0     1400.0
## 59:          1399.0     1789.0       3072.5     1395.0
## 60:          1400.0     1750.0       3000.0     1395.0
## 61:          1400.0     1789.0       3000.0     1399.0
## 62:          1399.0     1800.0       3100.0     1400.0
## 63:          1400.0     1845.0       3200.0     1400.0
## 64:          1425.0     1850.0       3200.0     1450.0
## 65:          1450.0     1895.0       3352.5     1495.0
## 66:          1456.5     1895.0       3500.0     1500.0
## 67:          1450.0     1895.0       3500.0     1525.0
## 68:          1450.0     1929.0       3500.0     1525.0
## 69:          1450.0     1900.0       3500.0     1525.0
## 70:          1450.0     1895.0       3495.0     1532.5
## 71:          1450.0     1850.0       3400.0     1529.0
## 72:          1450.0     1850.0       3300.0     1500.0
## 73:          1475.0     1895.0       3395.0     1500.0
## 74:          1475.0     1895.0       3495.0     1500.0
## 75:          1480.0     1900.0       3450.0     1500.0
## 76:          1450.0     1890.0       3400.0     1450.0
## 77:          1450.0     1900.0       3500.0     1450.0
## 78:          1475.0     1900.0       3495.0     1495.0
## 79:          1495.0     1895.0       3500.0     1499.0
## 80:          1450.0     1900.0       3400.0     1499.0
## 81:          1450.0     1850.0       3300.0     1445.0
## 82:          1450.0     1850.0       3292.5     1400.0
## 83:          1495.0     1800.0       3200.0     1400.0
## 84:          1450.0     1800.0       3200.0     1400.0
## 85:          1497.0     1850.0       3250.0     1500.0
## 86:          1500.0     1895.0       3300.0     1550.0
## 87:          1525.0     1900.0       3399.5     1595.0
## 88:          1529.5     1950.0       3450.0     1625.0
## 89:          1575.0     1995.0       3500.0     1650.0
## 90:          1579.0     1995.0       3600.0     1650.0
## 91:          1595.0     1995.0       3600.0     1650.0
## 92:          1595.0     1950.0       3500.0     1625.0
## 93:          1595.0     1950.0       3500.0     1600.0
## 94:          1563.0     1950.0       3480.0     1600.0
## 95:          1600.0     1950.0       3400.0     1595.0
## 96:          1600.0     1950.0       3450.0     1595.0
## 97:          1600.0     1950.0       3480.0     1595.0
## 98:          1600.0     1995.0       3485.0     1600.0
##     Minneapolis, MN Denver, CO San Jose, CA Austin, TX
ny <- ggplot(tmetro, aes(x = as.Date(RegionName), y = tmetro$`New York, NY`, group=1)) + 
  geom_line() + theme_minimal()+ xlab("Date") + ylab("Rent Price in USD")+scale_x_date(date_breaks = "1 year", date_labels = "%Y")
ny

d <- melt(tmetro, id.vars="RegionName")
## Warning in melt.data.table(tmetro, id.vars = "RegionName"):
## 'measure.vars' [New York, NY, Los Angeles, CA, Chicago, IL, Dallas,
## TX, ...] are not all of the same type. By order of hierarchy, the molten
## data value column will be of type 'double'. All measure variables not of
## type 'double' will be coerced to. Check DETAILS in ?melt.data.table for
## more on coercion.
# Everything on the same plot
time <- ggplot(d, aes(as.Date(RegionName),value, col=variable, group=1)) + 
  geom_line() + theme(axis.text.x = element_text(angle = 90, hjust = 1))+
  scale_x_date(date_breaks = "1 year", date_labels = "%Y")+ xlab("Date") + ylab("Rent Price in USD")+ theme_minimal()
ggplotly(time)
## We recommend that you use the dev version of ggplot2 with `ggplotly()`
## Install it with: `devtools::install_github('hadley/ggplot2')`
mtime <-time +
  facet_wrap(~variable)+
  theme(axis.title.x=element_blank(),
        axis.text.x=element_blank(),
        axis.ticks.x=element_blank())+ xlab("Date") + ylab("Rent Price in USD")
ggplotly(mtime)
## We recommend that you use the dev version of ggplot2 with `ggplotly()`
## Install it with: `devtools::install_github('hadley/ggplot2')`
mmetro <- tmetro


mmetro
##     RegionName New York, NY Los Angeles, CA Chicago, IL Dallas, TX
##  1: 2010-01-01         2150              NA          NA         NA
##  2: 2010-02-01         2000          2495.0      1550.0     1250.0
##  3: 2010-03-01         2300          2400.0      1500.0     1300.0
##  4: 2010-04-01         2500          2462.5      1500.0     1400.0
##  5: 2010-05-01         2400          2500.0      1500.0     1350.0
##  6: 2010-06-01         2650          2500.0      1500.0     1350.0
##  7: 2010-07-01         2495          2699.5      1550.0     1350.0
##  8: 2010-08-01         2300          2800.0      1500.0     1350.0
##  9: 2010-09-01         2300          2600.0      1500.0     1375.0
## 10: 2010-10-01         2500          2500.0      1560.0     1400.0
## 11: 2010-11-01         2500          2500.0      1575.0     1395.0
## 12: 2010-12-01         2800          2500.0      1600.0     1400.0
## 13: 2011-01-01         2500          2495.0      1550.0     1375.0
## 14: 2011-02-01         2400          2450.0      1525.0     1300.0
## 15: 2011-03-01         2500          2450.0      1500.0     1300.0
## 16: 2011-04-01         2700          2500.0      1550.0     1325.0
## 17: 2011-05-01         2700          2500.0      1585.0     1350.0
## 18: 2011-06-01         2700          2500.0      1600.0     1350.0
## 19: 2011-07-01         2700          2500.0      1600.0     1350.0
## 20: 2011-08-01         2700          2500.0      1600.0     1300.0
## 21: 2011-09-01         2600          2500.0      1600.0     1295.0
## 22: 2011-10-01         2500          2400.0      1550.0     1250.0
## 23: 2011-11-01         2500          2300.0      1500.0     1250.0
## 24: 2011-12-01         2500          2300.0      1500.0     1250.0
## 25: 2012-01-01         2400          2300.0      1500.0     1250.0
## 26: 2012-02-01         2535          2350.0      1500.0     1295.0
## 27: 2012-03-01         2500          2300.0      1550.0     1300.0
## 28: 2012-04-01         2500          2295.0      1500.0     1200.0
## 29: 2012-05-01         2595          2350.0      1500.0     1250.0
## 30: 2012-06-01         2550          2350.0      1550.0     1295.0
## 31: 2012-07-01         2599          2300.0      1550.0     1257.0
## 32: 2012-08-01         2575          2250.0      1550.0     1250.0
## 33: 2012-09-01         2595          2300.0      1500.0     1250.0
## 34: 2012-10-01         2600          2200.0      1500.0     1250.0
## 35: 2012-11-01         2600          2150.0      1500.0     1273.5
## 36: 2012-12-01         2750          2100.0      1500.0     1250.0
## 37: 2013-01-01         2700          2175.0      1500.0     1225.0
## 38: 2013-02-01         2750          2200.0      1500.0     1250.0
## 39: 2013-03-01         2750          2150.0      1500.0     1250.0
## 40: 2013-04-01         2800          2200.0      1500.0     1250.0
## 41: 2013-05-01         2850          2200.0      1550.0     1275.0
## 42: 2013-06-01         2800          2250.0      1550.0     1350.0
## 43: 2013-07-01         2695          2200.0      1582.5     1350.0
## 44: 2013-08-01         2700          2050.0      1595.0     1300.0
## 45: 2013-09-01         2700          2300.0      1596.5     1345.0
## 46: 2013-10-01         2600          2400.0      1600.0     1350.0
## 47: 2013-11-01         2650          2300.0      1595.0     1325.0
## 48: 2013-12-01         2750          2450.0      1600.0     1350.0
## 49: 2014-01-01         2775          2400.0      1595.0     1350.0
## 50: 2014-02-01         2750          2400.0      1557.0     1350.0
## 51: 2014-03-01         2700          2400.0      1550.0     1350.0
## 52: 2014-04-01         2675          2400.0      1550.0     1350.0
## 53: 2014-05-01         2800          2500.0      1600.0     1400.0
## 54: 2014-06-01         2850          2550.0      1650.0     1400.0
## 55: 2014-07-01         2750          2600.0      1650.0     1450.0
## 56: 2014-08-01         2700          2600.0      1650.0     1450.0
## 57: 2014-09-01         2650          2600.0      1650.0     1445.0
## 58: 2014-10-01         2600          2600.0      1650.0     1424.0
## 59: 2014-11-01         2600          2600.0      1600.0     1445.0
## 60: 2014-12-01         2650          2650.0      1609.0     1450.0
## 61: 2015-01-01         2795          2650.0      1600.0     1450.0
## 62: 2015-02-01         2795          2650.0      1625.0     1450.0
## 63: 2015-03-01         2800          2685.0      1649.0     1495.0
## 64: 2015-04-01         2900          2750.0      1650.0     1500.0
## 65: 2015-05-01         2800          2795.0      1650.0     1500.0
## 66: 2015-06-01         2850          2800.0      1650.0     1500.0
## 67: 2015-07-01         2900          2800.0      1665.0     1550.0
## 68: 2015-08-01         2900          2850.0      1675.0     1525.0
## 69: 2015-09-01         2900          2800.0      1650.0     1500.0
## 70: 2015-10-01         2800          2800.0      1609.0     1500.0
## 71: 2015-11-01         2850          2800.0      1645.0     1500.0
## 72: 2015-12-01         2900          2800.0      1600.0     1500.0
## 73: 2016-01-01         2950          2800.0      1605.0     1500.0
## 74: 2016-02-01         2899          2875.0      1645.0     1500.0
## 75: 2016-03-01         2950          2900.0      1650.0     1550.0
## 76: 2016-04-01         3000          2850.0      1650.0     1550.0
## 77: 2016-05-01         3000          2800.0      1650.0     1550.0
## 78: 2016-06-01         2900          2895.0      1650.0     1575.0
## 79: 2016-07-01         2800          2850.0      1650.0     1595.0
## 80: 2016-08-01         2700          2800.0      1650.0     1595.0
## 81: 2016-09-01         2800          2870.0      1600.0     1545.0
## 82: 2016-10-01         2800          2790.0      1600.0     1525.0
## 83: 2016-11-01         2750          2900.0      1600.0     1595.0
## 84: 2016-12-01         2700          2750.0      1600.0     1525.0
## 85: 2017-01-01         2700          2850.0      1600.0     1595.0
## 86: 2017-02-01         2750          2950.0      1600.0     1599.0
## 87: 2017-03-01         2850          3000.0      1625.0     1625.0
## 88: 2017-04-01         2975          3050.0      1650.0     1675.0
## 89: 2017-05-01         3000          3100.0      1695.0     1695.0
## 90: 2017-06-01         3000          3100.0      1700.0     1700.0
## 91: 2017-07-01         2950          3100.0      1700.0     1700.0
## 92: 2017-08-01         2895          3095.0      1700.0     1695.0
## 93: 2017-09-01         3195          3000.0      1695.0     1695.0
## 94: 2017-10-01         2950          3000.0      1650.0     1650.0
## 95: 2017-11-01         2950          3000.0      1650.0     1650.0
## 96: 2017-12-01         3000          3000.0      1650.0     1650.0
## 97: 2018-01-01         2950          3000.0      1650.0     1650.0
## 98: 2018-02-01         3000          3000.0      1650.0     1650.0
##     RegionName New York, NY Los Angeles, CA Chicago, IL Dallas, TX
##     Philadelphia, PA Houston, TX Washington, DC Miami, FL Atlanta, GA
##  1:               NA          NA             NA        NA      1012.5
##  2:           1500.0          NA           1650        NA      1150.0
##  3:           1500.0          NA           1700    1800.0      1195.0
##  4:           1497.0          NA           1750    1800.0      1200.0
##  5:           1500.0          NA           1750    1800.0      1200.0
##  6:           1537.5          NA           1800    1800.0      1200.0
##  7:           1500.0          NA           1900    1900.0      1200.0
##  8:           1500.0          NA           1875    1900.0      1200.0
##  9:           1500.0          NA           1800    1900.0      1200.0
## 10:           1495.0          NA           1800    1800.0      1200.0
## 11:           1500.0          NA           1800    1750.0      1200.0
## 12:           1500.0          NA           1800    1800.0      1200.0
## 13:           1400.0          NA           1800    1700.0      1175.0
## 14:           1400.0          NA           1800    1650.0      1150.0
## 15:           1400.0          NA           1800    1650.0      1150.0
## 16:           1500.0          NA           1845    1699.5      1195.0
## 17:           1500.0          NA           1900    1700.0      1200.0
## 18:           1500.0          NA           1950    1700.0      1200.0
## 19:           1500.0          NA           1945    1700.0      1150.0
## 20:           1500.0          NA           1900    1700.0      1150.0
## 21:           1500.0          NA           1900    1700.0      1100.0
## 22:           1450.0          NA           1900    1700.0      1100.0
## 23:           1400.0          NA           1850    1700.0      1099.0
## 24:           1400.0          NA           1850    1675.0      1100.0
## 25:           1400.0          NA           1825    1650.0      1050.0
## 26:           1400.0          NA           1800    1650.0      1050.0
## 27:           1450.0          NA           1850    1697.0      1085.0
## 28:           1450.0          NA           1895    1650.0      1040.0
## 29:           1450.0          NA           1925    1650.0      1050.0
## 30:           1450.0          NA           1990    1700.0      1095.0
## 31:           1400.0          NA           1975    1690.0      1095.0
## 32:           1400.0          NA           1950    1695.0      1050.0
## 33:           1375.0          NA           1900    1650.0      1075.0
## 34:           1380.0          NA           1900    1650.0      1050.0
## 35:           1375.0          NA           1900    1650.0      1000.0
## 36:           1350.0          NA           1899    1650.0      1000.0
## 37:           1350.0          NA           1895    1650.0      1000.0
## 38:           1350.0          NA           1900    1650.0       995.0
## 39:           1375.0          NA           1900    1650.0      1015.0
## 40:           1400.0          NA           1900    1695.0      1045.0
## 41:           1450.0          NA           1900    1700.0      1095.0
## 42:           1400.0          NA           1995    1750.0      1095.0
## 43:           1400.0          NA           1975    1800.0      1095.0
## 44:           1400.0          NA           1960    1800.0      1050.0
## 45:           1400.0          NA           1950    1800.0      1095.0
## 46:           1425.0          NA           1950    1850.0      1100.0
## 47:           1400.0      1375.0           1950    1875.0      1090.0
## 48:           1400.0      1395.0           1900    1900.0      1100.0
## 49:           1400.0      1375.0           1900    1850.0      1095.0
## 50:           1375.0      1355.0           1900    1850.0      1095.0
## 51:           1395.0      1395.0           1900    1800.0      1095.0
## 52:           1400.0      1450.0           1900    1800.0      1095.0
## 53:           1500.0      1500.0           1995    1850.0      1100.0
## 54:           1500.0      1550.0           2000    1850.0      1100.0
## 55:           1500.0      1550.0           2000    1875.0      1125.0
## 56:           1500.0      1575.0           2000    1850.0      1149.0
## 57:           1495.0      1550.0           2000    1850.0      1149.0
## 58:           1475.0      1525.0           1980    1850.0      1150.0
## 59:           1450.0      1550.0           1950    1850.0      1150.0
## 60:           1450.0      1550.0           1950    1850.0      1125.0
## 61:           1450.0      1550.0           1950    1850.0      1125.0
## 62:           1495.0      1550.0           1950    1850.0      1145.0
## 63:           1500.0      1575.0           1975    1900.0      1175.0
## 64:           1500.0      1600.0           1995    1900.0      1200.0
## 65:           1550.0      1600.0           2000    1950.0      1200.0
## 66:           1550.0      1650.0           2050    2000.0      1250.0
## 67:           1550.0      1625.0           2050    2000.0      1245.0
## 68:           1500.0      1600.0           2050    2000.0      1200.0
## 69:           1500.0      1600.0           2000    1995.0      1200.0
## 70:           1500.0      1600.0           1999    2000.0      1200.0
## 71:           1500.0      1600.0           1995    2000.0      1200.0
## 72:           1475.0      1600.0           1995    2000.0      1200.0
## 73:           1495.0      1600.0           1995    2000.0      1225.0
## 74:           1500.0      1600.0           1999    2000.0      1240.0
## 75:           1500.0      1645.0           2000    2000.0      1250.0
## 76:           1550.0      1650.0           2000    2000.0      1260.0
## 77:           1550.0      1600.0           2050    2000.0      1300.0
## 78:           1525.0      1600.0           2050    2000.0      1300.0
## 79:           1500.0      1575.0           2100    1950.0      1300.0
## 80:           1500.0      1585.0           2099    1900.0      1295.0
## 81:           1500.0      1556.5           2000    1950.0      1295.0
## 82:           1450.0      1500.0           2000    1950.0      1300.0
## 83:           1495.0      1505.0           1999    2000.0      1300.0
## 84:           1450.0      1495.0           1999    1875.0      1295.0
## 85:           1450.0      1525.0           2000    1930.0      1300.0
## 86:           1450.0      1550.0           2000    1950.0      1345.0
## 87:           1500.0      1550.0           2000    1975.0      1350.0
## 88:           1550.0      1595.0           2100    1995.0      1400.0
## 89:           1550.0      1600.0           2150    2000.0      1400.0
## 90:           1550.0      1600.0           2195    2000.0      1418.5
## 91:           1550.0      1600.0           2200    2000.0      1445.0
## 92:           1500.0      1600.0           2150    2000.0      1400.0
## 93:           1500.0      1600.0           2100    2000.0      1400.0
## 94:           1500.0      1595.0           2050    2000.0      1395.0
## 95:           1500.0      1590.0           2000    2000.0      1395.0
## 96:           1500.0      1595.0           2000    2000.0      1395.0
## 97:           1500.0      1575.0           2000    2000.0      1400.0
## 98:           1500.0      1591.0           2000    2000.0      1400.0
##     Philadelphia, PA Houston, TX Washington, DC Miami, FL Atlanta, GA
##     Boston, MA San Francisco, CA Detroit, MI Phoenix, AZ Seattle, WA
##  1:         NA            2600.0          NA          NA      1200.0
##  2:         NA            2250.0          NA          NA      1395.0
##  3:     1375.0            2200.0          NA        1500      1495.0
##  4:     1500.0            2250.0          NA        1495      1500.0
##  5:     1475.0            2600.0          NA        1400      1500.0
##  6:     1552.5            2500.0          NA        1350      1595.0
##  7:     1597.5            2575.0          NA        1300      1600.0
##  8:     1600.0            2397.5          NA        1300      1685.0
##  9:     1600.0            2150.0          NA        1295      1600.0
## 10:     1600.0            2150.0          NA        1275      1595.0
## 11:     1691.0            2100.0          NA        1275      1550.0
## 12:     1695.0            2200.0          NA        1250      1499.5
## 13:     1747.5            2000.0          NA        1195      1550.0
## 14:     1707.5            2050.0          NA        1175      1500.0
## 15:     1747.5            2095.0          NA        1150      1500.0
## 16:     1850.0            2100.0          NA        1195      1525.0
## 17:     1900.0            2075.0          NA        1195      1595.0
## 18:     1900.0            2100.0          NA        1175      1595.0
## 19:     1975.0            2167.5          NA        1125      1595.0
## 20:     1900.0            2150.0          NA        1100      1550.0
## 21:     1900.0            2150.0          NA        1100      1550.0
## 22:     1837.5            2150.0          NA        1100      1500.0
## 23:     1850.0            2150.0       800.0        1095      1450.0
## 24:     1850.0            2050.0       850.0        1095      1401.5
## 25:     1900.0            2000.0       850.0        1099      1400.0
## 26:     1950.0            2095.0       850.0        1095      1400.0
## 27:     2000.0            2200.0       850.0        1100      1450.0
## 28:     2000.0            1995.0       850.0        1100      1450.0
## 29:     2050.0            1950.0       850.0        1120      1475.0
## 30:     2100.0            2050.0       850.0        1150      1495.0
## 31:     2100.0            2000.0       850.0        1125      1495.0
## 32:     2000.0            1995.0       895.0        1100      1495.0
## 33:     2150.0            2000.0       875.0        1100      1475.0
## 34:     2100.0            2000.0       850.0        1100      1450.0
## 35:     2100.0            2000.0       850.0        1095      1407.5
## 36:     2070.0            2000.0       850.0        1095      1395.0
## 37:     2200.0            2000.0       850.0        1098      1395.0
## 38:     2200.0            2000.0       850.0        1095      1385.0
## 39:     2200.0            2000.0       850.0        1100      1395.0
## 40:     2250.0            1995.0       850.0        1100      1449.0
## 41:     2250.0            2000.0       870.0        1100      1495.0
## 42:     2297.0            2000.0       850.0        1100      1525.0
## 43:     2300.0            2050.0       875.0        1100      1500.0
## 44:     2250.0            2000.0       875.0        1070      1550.0
## 45:     2200.0            2200.0       899.0        1100      1595.0
## 46:     2325.0            2200.0       899.0        1100      1625.0
## 47:     2300.0            2200.0       900.0        1100      1625.0
## 48:     2300.0            2300.0       900.0        1100      1600.0
## 49:     2310.0            2295.0       900.0        1100      1595.0
## 50:     2300.0            2250.0       895.0        1100      1595.0
## 51:     2300.0            2275.0       895.0        1100      1595.0
## 52:     2350.0            2300.0       899.0        1125      1595.0
## 53:     2500.0            2500.0       900.0        1200      1650.0
## 54:     2500.0            2500.0       900.0        1200      1650.0
## 55:     2500.0            2650.0       900.0        1200      1695.0
## 56:     2450.0            2700.0       925.0        1200      1700.0
## 57:     2400.0            2700.0       900.0        1200      1695.0
## 58:     2365.0            2700.0       925.0        1200      1695.0
## 59:     2325.0            2750.0       925.0        1200      1695.0
## 60:     2400.0            2750.0       925.0        1200      1690.0
## 61:     2500.0            2700.0       900.0        1200      1675.0
## 62:     2500.0            2799.5       900.0        1250      1690.0
## 63:     2500.0            2850.0       912.5        1290      1695.0
## 64:     2500.0            2922.5       950.0        1299      1695.0
## 65:     2500.0            3000.0       950.0        1299      1750.0
## 66:     2500.0            3100.0       950.0        1300      1795.0
## 67:     2500.0            3200.0       950.0        1295      1850.0
## 68:     2500.0            3100.0       950.0        1295      1895.0
## 69:     2450.0            3100.0       950.0        1295      1850.0
## 70:     2400.0            3150.0       950.0        1275      1850.0
## 71:     2400.0            3150.0       950.0        1295      1850.0
## 72:     2499.5            3154.5       950.0        1300      1850.0
## 73:     2600.0            3200.0       950.0        1300      1850.0
## 74:     2600.0            3250.0       950.0        1325      1850.0
## 75:     2600.0            3300.0       975.0        1350      1850.0
## 76:     2550.0            3300.0      1000.0        1350      1850.0
## 77:     2500.0            3250.0      1000.0        1300      1900.0
## 78:     2600.0            3250.0      1000.0        1300      1975.0
## 79:     2500.0            3300.0      1100.0        1299      2000.0
## 80:     2500.0            3200.0      1095.0        1295      2000.0
## 81:     2500.0            3195.0      1000.0        1275      1995.0
## 82:     2450.0            3000.0      1049.0        1295      1950.0
## 83:     2400.0            3000.0      1040.0        1295      1949.5
## 84:     2450.0            2995.0      1000.0        1250      1900.0
## 85:     2500.0            3000.0      1000.0        1300      1995.0
## 86:     2600.0            3195.0       995.0        1325      2025.0
## 87:     2600.0            3200.0      1000.0        1350      2100.0
## 88:     2650.0            3300.0      1050.0        1399      2195.0
## 89:     2645.0            3400.0      1075.0        1400      2250.0
## 90:     2600.0            3400.0      1100.0        1400      2300.0
## 91:     2600.0            3400.0      1100.0        1400      2350.0
## 92:     2600.0            3400.0      1100.0        1400      2300.0
## 93:     2502.0            3300.0      1100.0        1395      2295.0
## 94:     2500.0            3295.0      1050.0        1395      2200.0
## 95:     2500.0            3200.0      1050.0        1395      2195.0
## 96:     2515.0            3200.0      1025.0        1395      2195.0
## 97:     2600.0            3200.0      1000.0        1395      2195.0
## 98:     2600.0            3200.0      1050.0        1400      2200.0
##     Boston, MA San Francisco, CA Detroit, MI Phoenix, AZ Seattle, WA
##     Minneapolis, MN Denver, CO San Jose, CA Austin, TX
##  1:              NA         NA           NA         NA
##  2:              NA         NA           NA         NA
##  3:              NA         NA           NA         NA
##  4:              NA         NA           NA         NA
##  5:              NA     1672.5           NA         NA
##  6:              NA     1392.5           NA         NA
##  7:              NA     1450.0           NA         NA
##  8:              NA     1390.0           NA         NA
##  9:          1400.0     1297.5           NA         NA
## 10:          1400.0     1250.0           NA         NA
## 11:          1399.0     1350.0           NA         NA
## 12:          1450.0     1300.0           NA         NA
## 13:          1300.0     1297.5           NA         NA
## 14:          1350.0     1300.0       2195.0         NA
## 15:          1350.0     1350.0       2295.0         NA
## 16:          1395.0     1350.0       2380.0         NA
## 17:          1385.0     1375.0       2380.0         NA
## 18:          1377.0     1350.0       2400.0         NA
## 19:          1395.0     1350.0       2500.0         NA
## 20:          1395.0     1350.0       2500.0         NA
## 21:          1390.0     1355.0       2495.0         NA
## 22:          1350.0     1350.0       2400.0         NA
## 23:          1300.0     1300.0       2395.0         NA
## 24:          1295.0     1295.0       2300.0         NA
## 25:          1295.0     1295.0       2250.0         NA
## 26:          1300.0     1295.0       2275.0         NA
## 27:          1300.0     1300.0       2300.0         NA
## 28:          1300.0     1395.0       2295.0         NA
## 29:          1300.0     1395.0       2250.0         NA
## 30:          1350.0     1400.0       2300.0         NA
## 31:          1325.0     1400.0       2400.0         NA
## 32:          1300.0     1400.0       2350.0         NA
## 33:          1375.0     1400.0       2350.0         NA
## 34:          1375.0     1375.0       2400.0         NA
## 35:          1300.0     1325.0       2300.0         NA
## 36:          1350.0     1310.0       2347.0         NA
## 37:          1350.0     1350.0       2370.0         NA
## 38:          1350.0     1350.0       2300.0     1100.0
## 39:          1350.0     1390.5       2295.5     1024.0
## 40:          1350.0     1450.0       2349.0     1090.0
## 41:          1350.0     1395.0       2400.0     1115.0
## 42:          1350.0     1395.0       2400.0     1281.5
## 43:          1300.0     1500.0       2500.0     1150.0
## 44:          1315.0     1475.0       2431.0     1199.0
## 45:          1375.0     1500.0       2650.0     1285.0
## 46:          1395.0     1575.0       2780.0     1349.0
## 47:          1400.0     1595.0       2775.0     1350.0
## 48:          1400.0     1600.0       2800.0     1326.0
## 49:          1400.0     1595.0       2695.0     1325.0
## 50:          1400.0     1575.0       2650.0     1350.0
## 51:          1395.0     1550.0       2650.0     1395.0
## 52:          1395.0     1595.0       2700.0     1419.5
## 53:          1395.0     1600.0       2995.0     1400.0
## 54:          1400.0     1695.0       3000.0     1400.0
## 55:          1400.0     1695.0       3095.0     1450.0
## 56:          1400.0     1700.0       3200.0     1450.0
## 57:          1400.0     1790.0       3150.0     1418.0
## 58:          1399.0     1754.5       3050.0     1400.0
## 59:          1399.0     1789.0       3072.5     1395.0
## 60:          1400.0     1750.0       3000.0     1395.0
## 61:          1400.0     1789.0       3000.0     1399.0
## 62:          1399.0     1800.0       3100.0     1400.0
## 63:          1400.0     1845.0       3200.0     1400.0
## 64:          1425.0     1850.0       3200.0     1450.0
## 65:          1450.0     1895.0       3352.5     1495.0
## 66:          1456.5     1895.0       3500.0     1500.0
## 67:          1450.0     1895.0       3500.0     1525.0
## 68:          1450.0     1929.0       3500.0     1525.0
## 69:          1450.0     1900.0       3500.0     1525.0
## 70:          1450.0     1895.0       3495.0     1532.5
## 71:          1450.0     1850.0       3400.0     1529.0
## 72:          1450.0     1850.0       3300.0     1500.0
## 73:          1475.0     1895.0       3395.0     1500.0
## 74:          1475.0     1895.0       3495.0     1500.0
## 75:          1480.0     1900.0       3450.0     1500.0
## 76:          1450.0     1890.0       3400.0     1450.0
## 77:          1450.0     1900.0       3500.0     1450.0
## 78:          1475.0     1900.0       3495.0     1495.0
## 79:          1495.0     1895.0       3500.0     1499.0
## 80:          1450.0     1900.0       3400.0     1499.0
## 81:          1450.0     1850.0       3300.0     1445.0
## 82:          1450.0     1850.0       3292.5     1400.0
## 83:          1495.0     1800.0       3200.0     1400.0
## 84:          1450.0     1800.0       3200.0     1400.0
## 85:          1497.0     1850.0       3250.0     1500.0
## 86:          1500.0     1895.0       3300.0     1550.0
## 87:          1525.0     1900.0       3399.5     1595.0
## 88:          1529.5     1950.0       3450.0     1625.0
## 89:          1575.0     1995.0       3500.0     1650.0
## 90:          1579.0     1995.0       3600.0     1650.0
## 91:          1595.0     1995.0       3600.0     1650.0
## 92:          1595.0     1950.0       3500.0     1625.0
## 93:          1595.0     1950.0       3500.0     1600.0
## 94:          1563.0     1950.0       3480.0     1600.0
## 95:          1600.0     1950.0       3400.0     1595.0
## 96:          1600.0     1950.0       3450.0     1595.0
## 97:          1600.0     1950.0       3480.0     1595.0
## 98:          1600.0     1995.0       3485.0     1600.0
##     Minneapolis, MN Denver, CO San Jose, CA Austin, TX
dygraph(mmetro, main = "Rent Prices in US metro area")%>%
  dyRangeSelector()%>%
  dyLegend(show = 'follow')
chartSeries(mmetro) 

lineChart(mmetro,line.type='h',TA=NULL) 

di <- d
cpi <- c(218.1,224.9,229.6,233.0, 236.7, 237.0, 240.0,244.7)
di$adj <- di$value
di$adj <- ifelse(substr(di$RegionName,1,4) == "2010", di$value*218.1/cpi[1], di$adj)
di$adj <- ifelse(substr(di$RegionName,1,4) == "2011", di$value*218.1/cpi[2], di$adj)
di$adj <- ifelse(substr(di$RegionName,1,4) == "2012", di$value*218.1/cpi[3], di$adj)
di$adj <- ifelse(substr(di$RegionName,1,4) == "2013", di$value*218.1/cpi[4], di$adj)
di$adj <- ifelse(substr(di$RegionName,1,4) == "2014", di$value*218.1/cpi[5], di$adj)
di$adj <- ifelse(substr(di$RegionName,1,4) == "2015", di$value*218.1/cpi[6], di$adj)
di$adj <- ifelse(substr(di$RegionName,1,4) == "2016", di$value*218.1/cpi[7], di$adj)
di$adj <- ifelse(substr(di$RegionName,1,4) == "2017", di$value*218.1/cpi[8], di$adj)
di$adj <- ifelse(substr(di$RegionName,1,4) == "2018", di$value*218.1/cpi[9], di$adj)

d
##       RegionName     variable value
##    1: 2010-01-01 New York, NY  2150
##    2: 2010-02-01 New York, NY  2000
##    3: 2010-03-01 New York, NY  2300
##    4: 2010-04-01 New York, NY  2500
##    5: 2010-05-01 New York, NY  2400
##   ---                              
## 1760: 2017-10-01   Austin, TX  1600
## 1761: 2017-11-01   Austin, TX  1595
## 1762: 2017-12-01   Austin, TX  1595
## 1763: 2018-01-01   Austin, TX  1595
## 1764: 2018-02-01   Austin, TX  1600
di
##       RegionName     variable value      adj
##    1: 2010-01-01 New York, NY  2150 2150.000
##    2: 2010-02-01 New York, NY  2000 2000.000
##    3: 2010-03-01 New York, NY  2300 2300.000
##    4: 2010-04-01 New York, NY  2500 2500.000
##    5: 2010-05-01 New York, NY  2400 2400.000
##   ---                                       
## 1760: 2017-10-01   Austin, TX  1600 1426.073
## 1761: 2017-11-01   Austin, TX  1595 1421.616
## 1762: 2017-12-01   Austin, TX  1595 1421.616
## 1763: 2018-01-01   Austin, TX  1595       NA
## 1764: 2018-02-01   Austin, TX  1600       NA
di$value <-di$adj
adj_time <- ggplot(di, aes(RegionName,value, col=variable, group=1)) + 
  geom_line() + theme(axis.text.x = element_text(angle = 90, hjust = 1))+
  scale_x_discrete(breaks = di$RegionName[seq(1, length(di$RegionName), by = 2)])+ xlab("Date") + ylab("Rent Price in USD")+ scale_x_date(date_breaks = "1 year", date_labels = "%Y-%m-%d")+ xlab("Date")
## Scale for 'x' is already present. Adding another scale for 'x', which
## will replace the existing scale.
ggplotly(adj_time)
## We recommend that you use the dev version of ggplot2 with `ggplotly()`
## Install it with: `devtools::install_github('hadley/ggplot2')`
nydata <- data.frame(rand = character(98))
nydata$date <- mmetro$RegionName
nydata$val <- mmetro$`New York, NY`


nydata$rand <- NULL
nydata
##          date  val
## 1  2010-01-01 2150
## 2  2010-02-01 2000
## 3  2010-03-01 2300
## 4  2010-04-01 2500
## 5  2010-05-01 2400
## 6  2010-06-01 2650
## 7  2010-07-01 2495
## 8  2010-08-01 2300
## 9  2010-09-01 2300
## 10 2010-10-01 2500
## 11 2010-11-01 2500
## 12 2010-12-01 2800
## 13 2011-01-01 2500
## 14 2011-02-01 2400
## 15 2011-03-01 2500
## 16 2011-04-01 2700
## 17 2011-05-01 2700
## 18 2011-06-01 2700
## 19 2011-07-01 2700
## 20 2011-08-01 2700
## 21 2011-09-01 2600
## 22 2011-10-01 2500
## 23 2011-11-01 2500
## 24 2011-12-01 2500
## 25 2012-01-01 2400
## 26 2012-02-01 2535
## 27 2012-03-01 2500
## 28 2012-04-01 2500
## 29 2012-05-01 2595
## 30 2012-06-01 2550
## 31 2012-07-01 2599
## 32 2012-08-01 2575
## 33 2012-09-01 2595
## 34 2012-10-01 2600
## 35 2012-11-01 2600
## 36 2012-12-01 2750
## 37 2013-01-01 2700
## 38 2013-02-01 2750
## 39 2013-03-01 2750
## 40 2013-04-01 2800
## 41 2013-05-01 2850
## 42 2013-06-01 2800
## 43 2013-07-01 2695
## 44 2013-08-01 2700
## 45 2013-09-01 2700
## 46 2013-10-01 2600
## 47 2013-11-01 2650
## 48 2013-12-01 2750
## 49 2014-01-01 2775
## 50 2014-02-01 2750
## 51 2014-03-01 2700
## 52 2014-04-01 2675
## 53 2014-05-01 2800
## 54 2014-06-01 2850
## 55 2014-07-01 2750
## 56 2014-08-01 2700
## 57 2014-09-01 2650
## 58 2014-10-01 2600
## 59 2014-11-01 2600
## 60 2014-12-01 2650
## 61 2015-01-01 2795
## 62 2015-02-01 2795
## 63 2015-03-01 2800
## 64 2015-04-01 2900
## 65 2015-05-01 2800
## 66 2015-06-01 2850
## 67 2015-07-01 2900
## 68 2015-08-01 2900
## 69 2015-09-01 2900
## 70 2015-10-01 2800
## 71 2015-11-01 2850
## 72 2015-12-01 2900
## 73 2016-01-01 2950
## 74 2016-02-01 2899
## 75 2016-03-01 2950
## 76 2016-04-01 3000
## 77 2016-05-01 3000
## 78 2016-06-01 2900
## 79 2016-07-01 2800
## 80 2016-08-01 2700
## 81 2016-09-01 2800
## 82 2016-10-01 2800
## 83 2016-11-01 2750
## 84 2016-12-01 2700
## 85 2017-01-01 2700
## 86 2017-02-01 2750
## 87 2017-03-01 2850
## 88 2017-04-01 2975
## 89 2017-05-01 3000
## 90 2017-06-01 3000
## 91 2017-07-01 2950
## 92 2017-08-01 2895
## 93 2017-09-01 3195
## 94 2017-10-01 2950
## 95 2017-11-01 2950
## 96 2017-12-01 3000
## 97 2018-01-01 2950
## 98 2018-02-01 3000
plot(forecast(auto.arima(nydata$val), h=100))

xnydata=xts(x = nydata$val, order.by = nydata$date)
dygraph(xnydata) %>%
  dyOptions( stemPlot=TRUE)
trend=nydata$val
cnydata=data.frame(time=nydata$date, open=shift(nydata$val, 1L, type="lag"), high=nydata$val+20, low=nydata$val-20, close=nydata$val)
cnydata=xts(x = cnydata[,-1], order.by = cnydata$time)

dygraph(cnydata) %>%
  dyCandlestick()
adj_time <- ggplot(di, aes(RegionName,value, col=variable, group=1, fill=variable)) + 
  geom_area() + theme(axis.text.x = element_text(angle = 90, hjust = 1))+
  scale_x_discrete(breaks = di$RegionName[seq(1, length(di$RegionName), by = 2)]) + xlab("Date") + ylab("Rent Price in USD")+scale_x_date(date_breaks = "1 year", date_labels = "%Y-%m-%d")
## Scale for 'x' is already present. Adding another scale for 'x', which
## will replace the existing scale.
ggplotly(adj_time)
## We recommend that you use the dev version of ggplot2 with `ggplotly()`
## Install it with: `devtools::install_github('hadley/ggplot2')`
## Warning: Removed 177 rows containing missing values (position_stack).
gnydata <- nydata
gnydata$growth <- with(gnydata, ave(val,
                      FUN=function(val) c(NA, diff(val)/val[-length(val)]) ))
gnydata
##          date  val       growth
## 1  2010-01-01 2150           NA
## 2  2010-02-01 2000 -0.069767442
## 3  2010-03-01 2300  0.150000000
## 4  2010-04-01 2500  0.086956522
## 5  2010-05-01 2400 -0.040000000
## 6  2010-06-01 2650  0.104166667
## 7  2010-07-01 2495 -0.058490566
## 8  2010-08-01 2300 -0.078156313
## 9  2010-09-01 2300  0.000000000
## 10 2010-10-01 2500  0.086956522
## 11 2010-11-01 2500  0.000000000
## 12 2010-12-01 2800  0.120000000
## 13 2011-01-01 2500 -0.107142857
## 14 2011-02-01 2400 -0.040000000
## 15 2011-03-01 2500  0.041666667
## 16 2011-04-01 2700  0.080000000
## 17 2011-05-01 2700  0.000000000
## 18 2011-06-01 2700  0.000000000
## 19 2011-07-01 2700  0.000000000
## 20 2011-08-01 2700  0.000000000
## 21 2011-09-01 2600 -0.037037037
## 22 2011-10-01 2500 -0.038461538
## 23 2011-11-01 2500  0.000000000
## 24 2011-12-01 2500  0.000000000
## 25 2012-01-01 2400 -0.040000000
## 26 2012-02-01 2535  0.056250000
## 27 2012-03-01 2500 -0.013806706
## 28 2012-04-01 2500  0.000000000
## 29 2012-05-01 2595  0.038000000
## 30 2012-06-01 2550 -0.017341040
## 31 2012-07-01 2599  0.019215686
## 32 2012-08-01 2575 -0.009234321
## 33 2012-09-01 2595  0.007766990
## 34 2012-10-01 2600  0.001926782
## 35 2012-11-01 2600  0.000000000
## 36 2012-12-01 2750  0.057692308
## 37 2013-01-01 2700 -0.018181818
## 38 2013-02-01 2750  0.018518519
## 39 2013-03-01 2750  0.000000000
## 40 2013-04-01 2800  0.018181818
## 41 2013-05-01 2850  0.017857143
## 42 2013-06-01 2800 -0.017543860
## 43 2013-07-01 2695 -0.037500000
## 44 2013-08-01 2700  0.001855288
## 45 2013-09-01 2700  0.000000000
## 46 2013-10-01 2600 -0.037037037
## 47 2013-11-01 2650  0.019230769
## 48 2013-12-01 2750  0.037735849
## 49 2014-01-01 2775  0.009090909
## 50 2014-02-01 2750 -0.009009009
## 51 2014-03-01 2700 -0.018181818
## 52 2014-04-01 2675 -0.009259259
## 53 2014-05-01 2800  0.046728972
## 54 2014-06-01 2850  0.017857143
## 55 2014-07-01 2750 -0.035087719
## 56 2014-08-01 2700 -0.018181818
## 57 2014-09-01 2650 -0.018518519
## 58 2014-10-01 2600 -0.018867925
## 59 2014-11-01 2600  0.000000000
## 60 2014-12-01 2650  0.019230769
## 61 2015-01-01 2795  0.054716981
## 62 2015-02-01 2795  0.000000000
## 63 2015-03-01 2800  0.001788909
## 64 2015-04-01 2900  0.035714286
## 65 2015-05-01 2800 -0.034482759
## 66 2015-06-01 2850  0.017857143
## 67 2015-07-01 2900  0.017543860
## 68 2015-08-01 2900  0.000000000
## 69 2015-09-01 2900  0.000000000
## 70 2015-10-01 2800 -0.034482759
## 71 2015-11-01 2850  0.017857143
## 72 2015-12-01 2900  0.017543860
## 73 2016-01-01 2950  0.017241379
## 74 2016-02-01 2899 -0.017288136
## 75 2016-03-01 2950  0.017592273
## 76 2016-04-01 3000  0.016949153
## 77 2016-05-01 3000  0.000000000
## 78 2016-06-01 2900 -0.033333333
## 79 2016-07-01 2800 -0.034482759
## 80 2016-08-01 2700 -0.035714286
## 81 2016-09-01 2800  0.037037037
## 82 2016-10-01 2800  0.000000000
## 83 2016-11-01 2750 -0.017857143
## 84 2016-12-01 2700 -0.018181818
## 85 2017-01-01 2700  0.000000000
## 86 2017-02-01 2750  0.018518519
## 87 2017-03-01 2850  0.036363636
## 88 2017-04-01 2975  0.043859649
## 89 2017-05-01 3000  0.008403361
## 90 2017-06-01 3000  0.000000000
## 91 2017-07-01 2950 -0.016666667
## 92 2017-08-01 2895 -0.018644068
## 93 2017-09-01 3195  0.103626943
## 94 2017-10-01 2950 -0.076682316
## 95 2017-11-01 2950  0.000000000
## 96 2017-12-01 3000  0.016949153
## 97 2018-01-01 2950 -0.016666667
## 98 2018-02-01 3000  0.016949153
gnydata<-gnydata %>% mutate(mycolor = ifelse(growth>0, "type2", "type1"))
ggplot(gnydata, aes(x=date, y=growth)) +
  geom_segment( aes(x=date, xend=date, y=0, yend=growth, color=mycolor), size=1.3, alpha=0.9) +
  theme_light() +
  theme(
    legend.position = "none",
    panel.border = element_blank(),
  ) +
  xlab("Date") +
  ylab("Rent Growth Rate")
## Warning: Removed 1 rows containing missing values (geom_segment).

ggplot(gnydata, aes(x=date, y=growth), group = 1) + geom_line()
## Warning: Removed 1 rows containing missing values (geom_path).